Recently, at least the following trends have emerged in the field of cellular telephony. First, mobile broadband traffic has been exploding in wireless networks such as WCDMA (wideband code division multiple access). The technical consequence is a corresponding steep increase of the interference in these networks, or equivalently, a steep increase of the load. This makes it important to exploit the load headroom that is left in the most efficient way.
Second, cellular networks are becoming more heterogeneous, with macro RBSs (radio base station) being supported by micro and pico RBSs at traffic hot spots. Furthermore, home base stations (e.g., femto RBSs) are emerging in many networks. This trend puts increasing demands on inter-cell interference management.
Third, the consequence of the above is a large increase of the number of network nodes in cellular networks, together with a reduced operator control. There is therefore a strong desire to introduce more self-organizing network (SON) functionality. Such functionality may support interference management by automatic interference threshold setting and adaptation, for a subset of the nodes of the cellular network.
To meet these new trends, high accuracy and high bandwidth load estimation becomes very important. Here, the high bandwidth, highly accurate estimation of the neighbor cell interference is troublesome, particularly in WCDMA networks. The neighbor cell interference in this context is the interference experienced at an own cell due to activities of cells other than the own cell. Thus, the neighbor cell interference may also be referred to as other cell interference.
Regarding the first trend, there does not yet exist a practical neighbor cell interference estimation algorithm that can, at the same time:                Provide neighbor cell interference estimates with an inaccuracy better than 10-20%; and        Does so with close to TTI (transmission time interval) bandwidth over interested power and load ranges.        
As a result, it is difficult or even impossible to make optimal scheduling decisions since the exact origin of the interference power in the uplink (UL) is unknown. In WCDMA for example, the UEs (user equipments) may or may not utilize the power granted by the EUL (enhanced uplink) scheduler. This leads to an inaccuracy of the load prediction step, where the scheduler bases its scheduling decision on a prediction of the resulting air interface load of the traffic it schedules. This is so since the 3GPP standard has an inherent delay of about at least 5 TTIs from the scheduling decision until the interference power appears over the air interface. Also soft and softer handover powers are estimated separately. This can lead to additional inaccuracies in the load prediction and estimation steps.
Regarding the second trend, there is currently no accurate and high bandwidth neighbor cell interference estimates available at the RBS level, or above RBS level in the WCDMA RAN, particularly for estimates cleaned from soft and soft handover powers. It is therefore difficult or even impossible to manage interference in heterogeneous networks (HetNets) in an optimal way. This is logical since different actions are needed depending on the origin of the interference power. This is easily understood in overload situations, since then the correct cell needs to receive power down commands, e.g., in the form of reduced thresholds to resolve the situation.
Regarding the third trend, there is currently no support for signalling of neighbor cell interference cleaned from softer handover powers, e.g., between NodeB and RNC, between RNCs, or directly between RBSs. There are therefore currently no algorithms in WCDMA that can account for and/or estimate interference impact factors between neighboring cells based on neighbor cell interference estimates gleaned from softer handover power.
Load Estimation Without Neighbor Cell Interference Estimation
Following is a discussion on measurement and estimation techniques to measure instantaneous total load on the uplink air interface given in a cell of a WCDMA system. In general, a load at the antenna connector is given by noise rise, also referred to as rise over thermal, RoT(t) , defined by:
                                          RoT            ⁡                          (              t              )                                =                                                    P                RTWP                            ⁡                              (                t                )                                                                    P                N                            ⁡                              (                t                )                                                    ,                            (        1        )            where PN(t) is the thermal noise level as measured at the antenna connector. For the purposes of discussion, PRTWP(t) may be viewed as the total wideband power defined by:
                                                        P              RTWP                        ⁡                          (              t              )                                =                                                    ∑                                  i                  =                  1                                I                            ⁢                                                          ⁢                                                P                  k                                ⁡                                  (                  t                  )                                                      +                                          P                neighbor                            ⁡                              (                t                )                                      +                                          P                N                            ⁡                              (                t                )                                                    ,                            (        2        )            also measured at the antenna connector. The total wideband power PRTWP(t) is unaffected by any de-spreading applied. In equation (2), Pneighbor(t) represents the power received from one or more cells of the WCDMA system other than an own cell, i.e., from neighbor cells. The Pi(t) is the power of the individual user i in the own cell. One major difficulty of any RoT estimation technique is the inability to separate the thermal noise PN(t)from the interference Pneighbor(t) from neighbor cells.
Another problem is that the signal reference points are, by definition, at the antenna connectors. The measurements are however obtained after the analog signal conditioning chain in the digital receiver. The analog signal conditioning chain introduces a scale factor error of about 1 dB (1-sigma) for which it is difficult to compensate. Fortunately, all powers of in equation (2) are equally affected by the scale factor error so when equation (1) is calculated, the scale factor error is cancelled as follows:
                                          RoT                                                                      ⁢              DigitalReceiver                                ⁡                      (            t            )                          =                                                            P                RTWP                DigitalReceiver                            ⁡                              (                t                )                                                                    P                N                DigitalReceiver                            ⁡                              (                t                )                                              =                                                                      γ                  ⁡                                      (                    t                    )                                                  ⁢                                                      P                    RTWP                    Antenna                                    ⁡                                      (                    t                    )                                                                                                γ                  ⁡                                      (                    t                    )                                                  ⁢                                                      P                    N                    Antenna                                    ⁡                                      (                    t                    )                                                                        =                                                            RoT                  Antenna                                ⁡                                  (                  t                  )                                            .                                                          (        3        )            
To understand the problem of interferences from neighboring cells when performing load estimation, note that:Pneighbor(t)+PN(t)=E└Pneighbor(t)┘+E[PN(t)]+ΔPneighbor(t)+ΔPN(t).  (4)where E[ ] denotes a mathematical expectation and where Δ denotes a variation around the mean.
The problem can now be seen. Since there are no measurements available in the RBS that are related to the neighbor cell interference, a linear filtering operation can at best estimate the sum E└Pneighbor(t)┘+E[PN(t)]. This estimate cannot be used to deduce the value of E[PN(t)]. The situation is the same as when the sum of two numbers is available. Then there is no way to determine the individual values of E└Pneighbor(t)┘ and E[PN(t)]. It has also been formally proved that the thermal noise power floor is not mathematically observable.
FIG. 1 illustrates a conventional algorithm that estimates a noise floor. The illustrated algorithm is referred to as a sliding window algorithm, and estimates the RoT as given by equation (1). The main problem solved by this conventional sliding window algorithm is that it can provide an accurate estimation of the thermal noise floor N(t). Since it is not possible to obtain exact estimates of this quantity due to the neighbor cell interference, the sliding window estimator therefore applies an approximation, by considering a soft minimum computed over a relative long window in time. Note that the sliding window estimator relies on the fact that the noise floor is constant over very long periods of time (disregarding small temperature drifts).
One significant disadvantage of the sliding window estimator is that the algorithm requires a large amount of memory. This becomes particularly troublesome in case a large number of instances of the algorithm is needed, as may be the case when the interference cancellation (IC) is introduced in the uplink.
A recursive algorithm has been introduced to reduce the memory consumption. Relative to the sliding window algorithm, the recursive algorithm can reduce the memory requirement by a factor of more than one hundred to a thousand.
Load Prediction Without Interference Power Estimation
Following is a discussion on techniques to predict instantaneous load on the uplink air interface ahead in time. The scheduler uses this functionality. The scheduler tests different combinations of grants to determine the best combinations, e.g., maximizing the throughput. This scheduling decision will only affect the air interface load after a number of TTIs (each such TTI being a predetermined time duration such as 2 or 10 ms for example), due to grant transmission latency and UE latency before the new grant takes effect over the air interface.
In a conventional SIR (signal-to-interference ratio) based method, the prediction of uplink load, for a tentative scheduled set of UEs and grants, is based on the power relation defined by:
                                                        P              RTWP                        ⁡                          (              t              )                                -                                    P              N                        ⁡                          (              t              )                                      =                                            ∑                              i                =                1                            N                        ⁢                                                  ⁢                                                            L                  i                                ⁡                                  (                  t                  )                                            ⁢                                                P                  RTWP                                ⁡                                  (                  t                  )                                                              +                                    P              neighbor                        ⁡                          (              t              )                                                          (        5        )            where Li(t) is the load factor of the i-th UE of the own cell. As indicated, Pneighbor(t) denotes the neighbor cell interference. The load factors of the own cell are computed as follows. First, note that:
                                                                        (                                  C                  /                  I                                )                            i                        ⁢                          (              t              )                                =                                                                      P                  i                                ⁡                                  (                  t                  )                                                                                                  P                    RTWP                                    ⁡                                      (                    t                    )                                                  -                                                      (                                          1                      -                      α                                        )                                    ⁢                                      P                    i                                                                        =                                                                                                      L                      i                                        ⁡                                          (                      t                      )                                                        ⁢                                                            P                      RTWP                                        ⁡                                          (                      t                      )                                                                                                                                  P                      RTWP                                        ⁡                                          (                      t                      )                                                        -                                                            (                                              1                        -                        α                                            )                                        ⁢                                                                  L                        i                                            ⁡                                              (                        t                        )                                                              ⁢                                                                  P                        RTWP                                            ⁡                                              (                        t                        )                                                                                                        =                                                                                                                  L                        i                                            ⁡                                              (                        t                        )                                                                                    1                      -                                                                        (                                                      1                            -                            α                                                    )                                                ⁢                                                                              L                            i                                                    ⁡                                                      (                            t                            )                                                                                                                                ⁢                                                                          ⁢                                                                          ⇔                                                                          ⁢                                                                          ⁢                                                            L                      i                                        ⁡                                          (                      t                      )                                                                      =                                                                                                    (                                                  C                          /                          I                                                )                                            i                                        ⁢                                          (                      t                      )                                                                            1                    +                                                                  (                                                  1                          -                          α                                                )                                            ⁢                                                                        (                                                      C                            /                            I                                                    )                                                i                                            ⁢                                              (                        t                        )                                                                                                                                ,                                  ⁢                                  ⁢                  i          =          1                ,        …        ⁢                                  ,        I        ,                            (        6        )            where I is the number of UEs in the own cell and α is the self-interference factor. The carrier-to-interference values, (C/I)i(t), i=1, . . . , I, are then related to the SINR (measured on the DPCCH channel) as follows:
                                                                        (                                  C                  /                  I                                )                            i                        ⁢                          (              t              )                                =                                                                      SINR                  i                                ⁡                                  (                  t                  )                                                            W                i                                      ⁢                          RxLoss              G                        ×                          (                              1                +                                                                                                    β                                                  DPDCH                          ,                          i                                                2                                            ⁡                                              (                        t                        )                                                              +                                                                  β                                                  EDPCCH                          ,                          i                                                2                                            ⁡                                              (                        t                        )                                                              +                                                                                            n                                                      codes                            ,                            i                                                                          ⁡                                                  (                          t                          )                                                                    ⁢                                                                        β                                                      EDPDCH                            ,                            i                                                    2                                                ⁡                                                  (                          t                          )                                                                                      +                                                                  β                                                  HSDPCCH                          ,                          i                                                2                                            ⁡                                              (                        t                        )                                                                                                                        β                      DPCCH                      2                                        ⁡                                          (                      t                      )                                                                                  )                                      ,                                  ⁢                                  ⁢                  i          =          1                ,        …        ⁢                                  ,                  I          .                                    (        7        )            
In equation (7), Wi represents the spreading factor, RxLoss represents the missed receiver energy, G represents the diversity gain and the β's represent the beta factors of the respective channels. Here, inactive channels are assumed to have zero data beta factors.
The UL load prediction then computes the uplink load of the own cell by a calculation of equations (6) and (7) for each UE of the own cell, followed by a summation:
                                                        L              own                        ⁡                          (              t              )                                =                                    ∑                              i                =                1                            I                        ⁢                                                  ⁢                                          L                i                            ⁡                              (                t                )                                                    ,                            (        8        )            which transforms equation (5) to:PRTWP(t)=Lown(t)PRTWP(t)+Pneighbor(t)+PN(t)   (9)Dividing equation (9) by PN(t) shows that the RoT can be predicted k TTIs ahead as:
                              RoT          ⁡                      (                          t              +              kT                        )                          =                                                                              P                  neighbor                                ⁡                                  (                  t                  )                                            /                                                P                  N                                ⁡                                  (                  t                  )                                                                    1              -                                                L                  own                                ⁡                                  (                  t                  )                                                              +                      1                          1              -                                                L                  own                                ⁡                                  (                  t                  )                                                                                        (        10        )            
In the SIR based load factor calculation, the load factor Li(t) is defined by equation (6). However, in a power based load factor calculation, the load factor Li(t) can be defined by:
                                                        L              i                        ⁡                          (              t              )                                =                                                    P                i                            ⁡                              (                t                )                                                                    P                RTWP                            ⁡                              (                t                )                                                    ,                                  ⁢                  i          =          1                ,        …        ⁢                                  ,        I        ,                            (        11        )            and equations (8)-(10) may be calculated based on the load factor Li(t) of equation (11) to predict the RoT k TTIs ahead. An advantage of the power based load factor calculation is that the parameter dependence is reduced. On the downside, a measurement of the UE power is needed. But in certain circumstances, the power based load factor calculation may be preferred.Heterogeneous Networks
In heterogeneous networks (HetNets), different kinds of cells are mixed. A problem that arises in HetNets in that the cells are likely to have different radio properties in terms of (among others):                radio sensitivity;        frequency band;        coverage;        output power;        capacity; and        acceptable load level.        
This can be an effect of the use of different RBS sizes (macro, micro, pico, femto), different revisions (different receiver technology, SW quality), different vendors, the purpose of a specific deployment, and so on. An important factor in HetNets is that of the air interface load management, i.e., the issues associated with the scheduling of radio resources in different cells and the interaction between cells in terms of inter-cell interference.
These issues are exemplified with reference to FIG. 2 which illustrates a low power cell with limited coverage intended to serve a hotspot. To enable sufficient coverage of the hot spot, an interference suppressing receiver like the G-rake+ is used. One problem is now that the low power cell is located in the interior of and at the boundary of a specific macro cell. Also, surrounding macro cells interfere with the low power cell rendering a high level of neighbor cell interference in the low power cell which, despite the advanced receiver, reduces the coverage to levels that do not allow coverage of the hot spot. As a result, UEs of the hot spot are connected to the surrounding macro cells, which can further increase the neighbor cell interference experienced by the low power cell.